For the training and evaluation of the proposed network, we use outdoor panoramic images from the SUN360 [1]} dataset.
We split the dataset into the training set (80%) and the testing set (20%).
The dataset contains around 40,000 images with different scene variations rendered in equirectangular format.
To accommodate the data with our framework, we render the panorama to a cube map format by warping it to the planar plane.
We split the viewing direction into the four horizontal sides of the cube.
The vertical center is located at 0, and the horizontal center is located at 0, 90 180, and 270.
The field of view for each horizontal view is the same, that is, it is generated randomly from 45 to 75. The images are normalized to [−1,1] for stability during training.
